Journal of Women & Aging, 26:113–126, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 0895-2841 print/1540-7322 online DOI: 10.1080/08952841.2014.885299
ARTICLES
Sleep Behaviors in Older African American Females Reporting Nonmalignant Chronic Pain: Understanding the Psychosocial Implications of General Sleep Disturbance TAMARA A. BAKER School of Aging Studies, University of South Florida, Tampa, FL
KEITH E. WHITFIELD Department of Psychology and Neuroscience, Duke University, Durham, NC
This study examined factors that influence sleep quality in older African American women ( N = 181) reporting chronic pain. Participants completed a series of questions assessing demographic and behavioral characteristics, health status, pain intensity, and sleep disturbance. Findings indicated that younger participants and those experiencing poorer physical functioning reported more difficulty sleeping due to pain. Similarly, participants who reported being awakened from sleep due to pain were younger and experienced greater pain intensity. Understanding the relationship between sleep and pain in this group of women may be useful in promoting effective disease management and sleep awareness among patients, caregivers, and healthcare professionals. KEYWORDS pain intensity, sleep disturbance, elderly, African Americans, physical functioning
Address correspondence to Tamara A. Baker, University of South Florida, School of Aging Studies, 4202 E Fowler, Avenue, MHC 1322, Tampa, FL 33620. E-mail: [email protected]
113
114
T. A. Baker and K. E. Whitfield
INTRODUCTION An estimated 50%–88% of patients with chronic nonmalignant pain report significant sleep disturbance (Chen, Hayman, Shmerling, Bean, & Leveille, 201; Morin, Gibson, & Wade, 1998). While it is recognized that sleep disturbance compromises quality of life and daily functioning, it may also lead to increased morbidities, mortality, and health-care utilization (AncoliIsrael, 2009; Magee, Caputi, & Iverson, 2011). Although cases of sleep disturbance are found across all age groups (Bromberg, Gil, Schanberg, 2011; Foley, Ancoli-Israel, Britz, & Walsh, 2004; McKnight-Eily et al., 2011; Palermo & Kiska, 2005; Simola et al., 2012), older adults are more likely to experience sleep-related disorders (e.g., restless leg syndrome, insomnia, sleep-disordered breathing, cognitive impairment; Ancoli-Israel, 2009; Gamaldo, Allaire, & Whitfield, 2008; Roepke & Ancoli-Osrael, 2010; Vaz Fragoso & Gill, 2007), and poor physical health (Bloom et al., 2009) than their younger-aged counterparts. Data from the National Sleep Foundation (NSF) show that older adults reporting four or more chronic illnesses are more likely to report their sleep quality as fair/poor (Foley et al., 2004). It was also found that females who reported their health as fair or poor were more likely to experience daytime sleepiness at least a few days a week, experience symptoms of a sleep disorder at least a few nights a week, or have been told by a doctor they have a sleep disorder (National Sleep Foundation, 2007a). In the same survey, bodily pain was similarly associated with reporting more sleep disturbances among the all-female sample. The relationship between pain and sleep quality is multifaceted and complex. This dyad is further complicated among patients diagnosed with medical conditions such as cancer (Anderson et al., 2003), hypertension, diabetes mellitus (Vaz Fragoso & Gill, 2007), and arthritis (rheumatoid and/or osteoarthritis; Louie, Tektonidou, Caban-Martínez, & Ward, 2011; Nicassio et al., 2012; Taylor-Gjevre, Gjevre, Nair, Skomro, & Lim, 2011). Cross-sectional and correlational studies involving clinical samples clearly show the significant relationship and bidirectional association between sleep and pain, suggesting that disturbed sleep may contribute to the onset or exacerbation of pain (O’Brien et al., 2011). While data support the relationship between pain and sleep disturbance among the aged and those reporting comorbid medical illnesses, there is a growing body of literature acknowledging the influence sleep disturbance has among females. Epidemiological evidence shows the impact of poor sleep quality on symptoms related to severe premenstrual syndrome (F. C. Baker et al., 2012), pre-, peri- and postmenopause (Ameratunga, Goldin, & Hickey, 2012; Eichling & Sahni, 2005; Kravitz et al., 2011; Ozisik-Karaman, Tanriverdi, & Degirmenci, 2012; Young, Rabago, Zqierska, Austin, & Laurel, 2003), postpartum (Kuo, Yang, Kuo, Tseng, & Tzeng, 2012; Newland, Fearing, Riley, & Neath, 2012), and varied musculoskeletal disorders (Shaver, Wilbur, Robinson, Wang, & Buntin, 2006; Theadom, Cropley, Parker, &
Sleep, Pain, and African American Females
115
Feigin, 2011) across the age continuum of females nationally and internationally (Kotronoulas, Wengström, & Kearney, 2011; Lindstrom, Andersson, Lintrup, Holst, & Berglund, 2012). In a survey of more than 1,000 females, the NSF (2007a) found that less than half (46%) of the participants reported sleep problems at least every night or almost every night. An estimated 50% reported waking up feeling “unrefreshed.” Data further showed that females (58%) were more likely to report “nighttime” pain than males (48%), with one in four females citing pain significantly interrupting their sleep (National Sleep Foundation, 2007b). While these data show the impact of poor sleep habits among majority populations, there is limited research providing a template for examining the association of health and behavioral indicators of sleep quality in older African American females. Examining sleep patterns specifically among this group provides invaluable information in explaining potential disparities in sleep quality and its impact on their overall quality of life. With the current study design, we examined the influence pain and other psychosocial indicators have on sleep quality among older African American females. These indicators have been identified and thoroughly examined (Anglin, Link, & Phelan, 2006; Durrence & Lichstein, 2006; Gallo, Bogner, Morales, & Ford, 2005) in comparison studies (primarily between Whites and Blacks); however; little attention has focused on racial comparisons without investigating the heterogeneity among Blacks (as a race group) or African Americans (as an ethnic group within the Black race). This approach is deliberately not comparative in nature; thus, the observed results may or may not be significantly different from other race groups. However, the research design provides detailed information about a group (African American females) of interest and emphasizes relationships that have not been addressed or researched in the past. Using a biopsychosocial theoretical approach (Whitfield, 2010), this exploratory study aimed to: (a) describe the type and frequency of selfreported sleep disturbance, (b) examine the association identified behavioral and physical health indicators have with sleep quality, and (c) quantify the influence of pain on sleep disturbance in a sample of older African American females.
MATERIALS AND METHODS Participants and Procedures This study used cross-sectional survey data taken from the Baltimore Study on Black Aging, a multistudy project designed to explore the association of health, cognition, and psychosocial variables in older community-dwelling African Americans (Whitfield, Baker-Thomas, Heyward, Gatto, & Williams, 1999). For study inclusion, the participant had to self-identify as African American (or Black), ≥ 50 years of age, doctor diagnosed with an arthritis condition (self-reported), able to provide consent, cognitively intact, and able
116
T. A. Baker and K. E. Whitfield
to read and understand English. All information was collected through structured interviews. This investigation was approved by the Pennsylvania State University’s Institutional Review Board (IRB).
Measures SLEEP INDICATORS Sleep disturbance was assessed with standardized single-itemed questions (“During the past have you had trouble falling asleep as a result of your pain?” and “During the past month have you been awakened by pain?”: always, sometimes, never) taken from the McGill Pain Questionnaire (MPQ; Melzack, 1975). Additional (MPQ) sleep parameters included: needing medication to fall asleep (“During the past month did you need medication to fall asleep?”) and factors (sleep/rest, lying down) that increase and/or decrease pain intensity. PREDICTOR
HEALTH VARIABLES
Pain intensity was evaluated using the Pain Rating Index (PRI) scale from the MPQ (Melzack, 1975). The PRI scale consists of 78 pain descriptors that provide an overall index of pain intensity (α = .72). A mean score value was obtained by summing the ranked intensities and then averaged to obtain a single score. Physical functioning was assessed using the Arthritis Impact Measurement Scale 2 (AIMS2; Meenan, Mason, Anderson, Guccione, & Kazis, 1992). The 25-item subscale score includes items on mobility, walking and bending, hand and finger function, arm function, self-care, and household tasks. The subscale yields a composite score ranging from 0 to 10, with higher scores indicating greater functional impairment (α = .90). The total number of pain locations was assessed by asking participants if pain was experienced in one of the following locations: knees, ankles, hips, shoulders, lower back, wrists, elbows, and hands. A total pain location score was derived by a count of the total number of body locations identified by each participant. The Medication Use Inventory Scale was used to assess the total number of medications (physician prescribed and/or over the counter) taken by each participant. A medication score was obtained by the total number of categories of medications reported (α = .69). A subscale of the Self-Evaluation of Life Function (SELF) was used to determine the count of chronic diseases (Linn & Linn, 1984). A total score was obtained by the count of chronic diseases (α = .52). Depressive symptoms were assessed using the Center for Epidemiological Studies-Depression scale (CES-D). Respondents are asked to indicate how often they experienced a given symptom within the past week. The measure yields a composite score ranging from 0 to 60,
Sleep, Pain, and African American Females
117
with high scores indicating more depressive symptoms. The CES-D has demonstrated acceptable internal consistency (α = .90) (Radloff, 1977). DEMOGRAPHIC CHARACTERISTICS Three demographic variables were included in the analyses: age, income, and education. Age was scored in a continuous format. Education was assessed as the total number of years of formal schooling. Income was coded dichotomously (earning < $1,000 a month). All participants were able to self-identify their race via nominal categories (e.g., Black/African American, White, Asian/Pacific Islander). While it is recognized that the term Black is a social construct to define race (Ford & Kelly, 2005), and African American as an ethnic group within the Black race, we combined the use of the terms, as many of the participants used the words interchangeably and did not make the distinction between the two. Therefore, those who self-identified as either Black or African American were included for study participation. STATISTICAL ANALYSIS Preliminary analyses were conducted to check for missing and outlying data. A series of Pearson Product-Moment correlation coefficients were calculated to determine a parsimonious model (p < .05) and to determine the strength of the bivariate associations between the sleep indices and each demographic, psychosocial, and health characteristic. A four-step hierarchical regression model was also used to examine the predictive utility of the demographic, pain, health, and psychosocial characteristics in sleep disturbance. Separate models were conducted for each sleep variable (difficulty falling asleep and awakened by pain). Variable inclusion in the final models were based on significance level (p < .05) in separate preliminary exploratory analyses. The first step in model development involved entering the demographic variables (age and education; Model I). Depression was entered on the second step (Model II). Pain locations, physical functioning, medication use, and comorbidities were entered in Model III, with pain intensity entered on the fourth step (Model IV). Standardized beta coefficients were reported to describe the relative importance of the predictor variables within each regression model. All statistical analyses were conducted using SPSS version 20.0 (SPSS Inc., Chicago, IL).
RESULTS Demographic and Sleep Characteristics The sample included 181 community-dwelling Black females, with a mean age of 71.1 ± 9.22 years and an average of 10.31 ± 2.87 years of education.
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T. A. Baker and K. E. Whitfield
TABLE 1 Sample Demographic and Sleep Characteristics (N = 181) Variables
M ± SD/%
Age Education Physical functioning Pain intensity Pain locations Medications Comorbidities Need medication to fall asleep∗ Trouble falling asleep∗ Awakened due to pain∗ Effect of sleep/rest on pain (decrease, increase, decrease & increase)
71.4 ± 9.22 10.31 ± 2.87 2.15 ± 1.56 28.6 ± 14.4 2.91 ± 1.45 5.60 ± 3.25 3.21 ± 1.72 28% 45% 53% 15% 13% 70% 25% 25% 49%
Effect of lying down on pain (decrease, increase, decrease & Increase)
∗
Sometimes.
Less than half (45%) of the sample reported sometimes having difficulty falling asleep, with 53% similarly reporting sometimes being awakened by pain. Seventy-one percent reported sleep/rest decreasing and increasing their pain intensity, with 49% reporting the effect of lying down both increasing and decreasing pain (Table 1). DIFFICULTY FALLING ASLEEP
AND
BEING AWAKENED DUE
TO
PAIN
Pearson product-moment correlations were used to examine the bivariate relationships between the predictor variables and sleep difficulty and being awakened from sleep due to pain. Table 2 shows a moderate association between difficulty falling asleep and age (r = –.31, p < .01) and pain intensity (r = .32, p < .01). Slightly lower, yet significant, relationships were similarly identified between difficulty falling asleep and comorbidities (r = TABLE 2 Association Between Sleep (Difficulty and Being Awakened by) and Psychosocial and Health Variables Variables (r) Age Physical functioning Pain intensity Depression Comorbidities Pain locations Medication ∗
p < .05;
∗∗
p < .01.
Difficulty Sleeping
Being Awakened
−.31∗∗ .29∗∗ .32∗∗ .25∗∗ .20∗ NS .17∗
−.23∗∗ .33∗∗ .40∗∗ .35∗∗ .26∗∗ .19∗ .29∗∗
Sleep, Pain, and African American Females
119
.20, p < .05), and medication use (r = .17, p < .05). An association was found for both sleep variables and physical functioning, with those experiencing greater physical disability reporting more difficulty falling asleep (r = .29, p < .01) and being awakened by pain (r = .33, p < .01). Experiencing more depressive symptoms was related to both sleep indices as well (difficulty falling asleep, r = .25, p < .01; being awakened by pain, r = .35, p < .01). Participants reporting being awakened due to pain were also likely to report more comorbid medical conditions (r = .26, p < .01), greater pain intensity (r = .40, p < .01), reporting more pain locations (r = .19, p < .05), and taking more medications (r = .29, p < .01). In addition, younger age (r = –.23, p < .01) and education (r = –.18, and education (r = –.18, p < .05) was similarly related to being awakened as a result of pain. No significant association was found with difficulty falling asleep and pain locations. There was also no significant relationship between income and either sleep variable.
INDICATORS
OF SLEEP DIFFICULTY
The first set of variables for model development (Model I) included the demographic variables that accounted for 11% of the total sleep variance, with age (β = –.32, p < .001) being the only significant predictor. Depression (β = .18, p < .05) was entered in the next step (Model II) and accounted for another 3% of the total variance. Age (β = –.29, p
ARTICLES
Sleep Behaviors in Older African American Females Reporting Nonmalignant Chronic Pain: Understanding the Psychosocial Implications of General Sleep Disturbance TAMARA A. BAKER School of Aging Studies, University of South Florida, Tampa, FL
KEITH E. WHITFIELD Department of Psychology and Neuroscience, Duke University, Durham, NC
This study examined factors that influence sleep quality in older African American women ( N = 181) reporting chronic pain. Participants completed a series of questions assessing demographic and behavioral characteristics, health status, pain intensity, and sleep disturbance. Findings indicated that younger participants and those experiencing poorer physical functioning reported more difficulty sleeping due to pain. Similarly, participants who reported being awakened from sleep due to pain were younger and experienced greater pain intensity. Understanding the relationship between sleep and pain in this group of women may be useful in promoting effective disease management and sleep awareness among patients, caregivers, and healthcare professionals. KEYWORDS pain intensity, sleep disturbance, elderly, African Americans, physical functioning
Address correspondence to Tamara A. Baker, University of South Florida, School of Aging Studies, 4202 E Fowler, Avenue, MHC 1322, Tampa, FL 33620. E-mail: [email protected]
113
114
T. A. Baker and K. E. Whitfield
INTRODUCTION An estimated 50%–88% of patients with chronic nonmalignant pain report significant sleep disturbance (Chen, Hayman, Shmerling, Bean, & Leveille, 201; Morin, Gibson, & Wade, 1998). While it is recognized that sleep disturbance compromises quality of life and daily functioning, it may also lead to increased morbidities, mortality, and health-care utilization (AncoliIsrael, 2009; Magee, Caputi, & Iverson, 2011). Although cases of sleep disturbance are found across all age groups (Bromberg, Gil, Schanberg, 2011; Foley, Ancoli-Israel, Britz, & Walsh, 2004; McKnight-Eily et al., 2011; Palermo & Kiska, 2005; Simola et al., 2012), older adults are more likely to experience sleep-related disorders (e.g., restless leg syndrome, insomnia, sleep-disordered breathing, cognitive impairment; Ancoli-Israel, 2009; Gamaldo, Allaire, & Whitfield, 2008; Roepke & Ancoli-Osrael, 2010; Vaz Fragoso & Gill, 2007), and poor physical health (Bloom et al., 2009) than their younger-aged counterparts. Data from the National Sleep Foundation (NSF) show that older adults reporting four or more chronic illnesses are more likely to report their sleep quality as fair/poor (Foley et al., 2004). It was also found that females who reported their health as fair or poor were more likely to experience daytime sleepiness at least a few days a week, experience symptoms of a sleep disorder at least a few nights a week, or have been told by a doctor they have a sleep disorder (National Sleep Foundation, 2007a). In the same survey, bodily pain was similarly associated with reporting more sleep disturbances among the all-female sample. The relationship between pain and sleep quality is multifaceted and complex. This dyad is further complicated among patients diagnosed with medical conditions such as cancer (Anderson et al., 2003), hypertension, diabetes mellitus (Vaz Fragoso & Gill, 2007), and arthritis (rheumatoid and/or osteoarthritis; Louie, Tektonidou, Caban-Martínez, & Ward, 2011; Nicassio et al., 2012; Taylor-Gjevre, Gjevre, Nair, Skomro, & Lim, 2011). Cross-sectional and correlational studies involving clinical samples clearly show the significant relationship and bidirectional association between sleep and pain, suggesting that disturbed sleep may contribute to the onset or exacerbation of pain (O’Brien et al., 2011). While data support the relationship between pain and sleep disturbance among the aged and those reporting comorbid medical illnesses, there is a growing body of literature acknowledging the influence sleep disturbance has among females. Epidemiological evidence shows the impact of poor sleep quality on symptoms related to severe premenstrual syndrome (F. C. Baker et al., 2012), pre-, peri- and postmenopause (Ameratunga, Goldin, & Hickey, 2012; Eichling & Sahni, 2005; Kravitz et al., 2011; Ozisik-Karaman, Tanriverdi, & Degirmenci, 2012; Young, Rabago, Zqierska, Austin, & Laurel, 2003), postpartum (Kuo, Yang, Kuo, Tseng, & Tzeng, 2012; Newland, Fearing, Riley, & Neath, 2012), and varied musculoskeletal disorders (Shaver, Wilbur, Robinson, Wang, & Buntin, 2006; Theadom, Cropley, Parker, &
Sleep, Pain, and African American Females
115
Feigin, 2011) across the age continuum of females nationally and internationally (Kotronoulas, Wengström, & Kearney, 2011; Lindstrom, Andersson, Lintrup, Holst, & Berglund, 2012). In a survey of more than 1,000 females, the NSF (2007a) found that less than half (46%) of the participants reported sleep problems at least every night or almost every night. An estimated 50% reported waking up feeling “unrefreshed.” Data further showed that females (58%) were more likely to report “nighttime” pain than males (48%), with one in four females citing pain significantly interrupting their sleep (National Sleep Foundation, 2007b). While these data show the impact of poor sleep habits among majority populations, there is limited research providing a template for examining the association of health and behavioral indicators of sleep quality in older African American females. Examining sleep patterns specifically among this group provides invaluable information in explaining potential disparities in sleep quality and its impact on their overall quality of life. With the current study design, we examined the influence pain and other psychosocial indicators have on sleep quality among older African American females. These indicators have been identified and thoroughly examined (Anglin, Link, & Phelan, 2006; Durrence & Lichstein, 2006; Gallo, Bogner, Morales, & Ford, 2005) in comparison studies (primarily between Whites and Blacks); however; little attention has focused on racial comparisons without investigating the heterogeneity among Blacks (as a race group) or African Americans (as an ethnic group within the Black race). This approach is deliberately not comparative in nature; thus, the observed results may or may not be significantly different from other race groups. However, the research design provides detailed information about a group (African American females) of interest and emphasizes relationships that have not been addressed or researched in the past. Using a biopsychosocial theoretical approach (Whitfield, 2010), this exploratory study aimed to: (a) describe the type and frequency of selfreported sleep disturbance, (b) examine the association identified behavioral and physical health indicators have with sleep quality, and (c) quantify the influence of pain on sleep disturbance in a sample of older African American females.
MATERIALS AND METHODS Participants and Procedures This study used cross-sectional survey data taken from the Baltimore Study on Black Aging, a multistudy project designed to explore the association of health, cognition, and psychosocial variables in older community-dwelling African Americans (Whitfield, Baker-Thomas, Heyward, Gatto, & Williams, 1999). For study inclusion, the participant had to self-identify as African American (or Black), ≥ 50 years of age, doctor diagnosed with an arthritis condition (self-reported), able to provide consent, cognitively intact, and able
116
T. A. Baker and K. E. Whitfield
to read and understand English. All information was collected through structured interviews. This investigation was approved by the Pennsylvania State University’s Institutional Review Board (IRB).
Measures SLEEP INDICATORS Sleep disturbance was assessed with standardized single-itemed questions (“During the past have you had trouble falling asleep as a result of your pain?” and “During the past month have you been awakened by pain?”: always, sometimes, never) taken from the McGill Pain Questionnaire (MPQ; Melzack, 1975). Additional (MPQ) sleep parameters included: needing medication to fall asleep (“During the past month did you need medication to fall asleep?”) and factors (sleep/rest, lying down) that increase and/or decrease pain intensity. PREDICTOR
HEALTH VARIABLES
Pain intensity was evaluated using the Pain Rating Index (PRI) scale from the MPQ (Melzack, 1975). The PRI scale consists of 78 pain descriptors that provide an overall index of pain intensity (α = .72). A mean score value was obtained by summing the ranked intensities and then averaged to obtain a single score. Physical functioning was assessed using the Arthritis Impact Measurement Scale 2 (AIMS2; Meenan, Mason, Anderson, Guccione, & Kazis, 1992). The 25-item subscale score includes items on mobility, walking and bending, hand and finger function, arm function, self-care, and household tasks. The subscale yields a composite score ranging from 0 to 10, with higher scores indicating greater functional impairment (α = .90). The total number of pain locations was assessed by asking participants if pain was experienced in one of the following locations: knees, ankles, hips, shoulders, lower back, wrists, elbows, and hands. A total pain location score was derived by a count of the total number of body locations identified by each participant. The Medication Use Inventory Scale was used to assess the total number of medications (physician prescribed and/or over the counter) taken by each participant. A medication score was obtained by the total number of categories of medications reported (α = .69). A subscale of the Self-Evaluation of Life Function (SELF) was used to determine the count of chronic diseases (Linn & Linn, 1984). A total score was obtained by the count of chronic diseases (α = .52). Depressive symptoms were assessed using the Center for Epidemiological Studies-Depression scale (CES-D). Respondents are asked to indicate how often they experienced a given symptom within the past week. The measure yields a composite score ranging from 0 to 60,
Sleep, Pain, and African American Females
117
with high scores indicating more depressive symptoms. The CES-D has demonstrated acceptable internal consistency (α = .90) (Radloff, 1977). DEMOGRAPHIC CHARACTERISTICS Three demographic variables were included in the analyses: age, income, and education. Age was scored in a continuous format. Education was assessed as the total number of years of formal schooling. Income was coded dichotomously (earning < $1,000 a month). All participants were able to self-identify their race via nominal categories (e.g., Black/African American, White, Asian/Pacific Islander). While it is recognized that the term Black is a social construct to define race (Ford & Kelly, 2005), and African American as an ethnic group within the Black race, we combined the use of the terms, as many of the participants used the words interchangeably and did not make the distinction between the two. Therefore, those who self-identified as either Black or African American were included for study participation. STATISTICAL ANALYSIS Preliminary analyses were conducted to check for missing and outlying data. A series of Pearson Product-Moment correlation coefficients were calculated to determine a parsimonious model (p < .05) and to determine the strength of the bivariate associations between the sleep indices and each demographic, psychosocial, and health characteristic. A four-step hierarchical regression model was also used to examine the predictive utility of the demographic, pain, health, and psychosocial characteristics in sleep disturbance. Separate models were conducted for each sleep variable (difficulty falling asleep and awakened by pain). Variable inclusion in the final models were based on significance level (p < .05) in separate preliminary exploratory analyses. The first step in model development involved entering the demographic variables (age and education; Model I). Depression was entered on the second step (Model II). Pain locations, physical functioning, medication use, and comorbidities were entered in Model III, with pain intensity entered on the fourth step (Model IV). Standardized beta coefficients were reported to describe the relative importance of the predictor variables within each regression model. All statistical analyses were conducted using SPSS version 20.0 (SPSS Inc., Chicago, IL).
RESULTS Demographic and Sleep Characteristics The sample included 181 community-dwelling Black females, with a mean age of 71.1 ± 9.22 years and an average of 10.31 ± 2.87 years of education.
118
T. A. Baker and K. E. Whitfield
TABLE 1 Sample Demographic and Sleep Characteristics (N = 181) Variables
M ± SD/%
Age Education Physical functioning Pain intensity Pain locations Medications Comorbidities Need medication to fall asleep∗ Trouble falling asleep∗ Awakened due to pain∗ Effect of sleep/rest on pain (decrease, increase, decrease & increase)
71.4 ± 9.22 10.31 ± 2.87 2.15 ± 1.56 28.6 ± 14.4 2.91 ± 1.45 5.60 ± 3.25 3.21 ± 1.72 28% 45% 53% 15% 13% 70% 25% 25% 49%
Effect of lying down on pain (decrease, increase, decrease & Increase)
∗
Sometimes.
Less than half (45%) of the sample reported sometimes having difficulty falling asleep, with 53% similarly reporting sometimes being awakened by pain. Seventy-one percent reported sleep/rest decreasing and increasing their pain intensity, with 49% reporting the effect of lying down both increasing and decreasing pain (Table 1). DIFFICULTY FALLING ASLEEP
AND
BEING AWAKENED DUE
TO
PAIN
Pearson product-moment correlations were used to examine the bivariate relationships between the predictor variables and sleep difficulty and being awakened from sleep due to pain. Table 2 shows a moderate association between difficulty falling asleep and age (r = –.31, p < .01) and pain intensity (r = .32, p < .01). Slightly lower, yet significant, relationships were similarly identified between difficulty falling asleep and comorbidities (r = TABLE 2 Association Between Sleep (Difficulty and Being Awakened by) and Psychosocial and Health Variables Variables (r) Age Physical functioning Pain intensity Depression Comorbidities Pain locations Medication ∗
p < .05;
∗∗
p < .01.
Difficulty Sleeping
Being Awakened
−.31∗∗ .29∗∗ .32∗∗ .25∗∗ .20∗ NS .17∗
−.23∗∗ .33∗∗ .40∗∗ .35∗∗ .26∗∗ .19∗ .29∗∗
Sleep, Pain, and African American Females
119
.20, p < .05), and medication use (r = .17, p < .05). An association was found for both sleep variables and physical functioning, with those experiencing greater physical disability reporting more difficulty falling asleep (r = .29, p < .01) and being awakened by pain (r = .33, p < .01). Experiencing more depressive symptoms was related to both sleep indices as well (difficulty falling asleep, r = .25, p < .01; being awakened by pain, r = .35, p < .01). Participants reporting being awakened due to pain were also likely to report more comorbid medical conditions (r = .26, p < .01), greater pain intensity (r = .40, p < .01), reporting more pain locations (r = .19, p < .05), and taking more medications (r = .29, p < .01). In addition, younger age (r = –.23, p < .01) and education (r = –.18, and education (r = –.18, p < .05) was similarly related to being awakened as a result of pain. No significant association was found with difficulty falling asleep and pain locations. There was also no significant relationship between income and either sleep variable.
INDICATORS
OF SLEEP DIFFICULTY
The first set of variables for model development (Model I) included the demographic variables that accounted for 11% of the total sleep variance, with age (β = –.32, p < .001) being the only significant predictor. Depression (β = .18, p < .05) was entered in the next step (Model II) and accounted for another 3% of the total variance. Age (β = –.29, p
